Loop Before You Leap: What Recurrent Depth Can and Cannot Buy in Data-Limited Pretraining
Compares shared-layer recurrent transformers with standard models under limited language data, with and without image features. Separates parameter and compute comparisons and measures how data composition and visual input affect linguistic performance.
First public: · Added to this list: November 9, 2026
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Recurrent reasoning — Repeat parts of the model or keep intermediate information in memory while working through a problem. Some methods also learn how many passes to run.
Analysis and evaluation — Measure how well these methods work, investigate what their internal computation does, and identify where they fail. This includes experiments, studies of model internals, and mathematical results.